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Proteomic profiling of breast cancer metabolism identifies SHMT2 and ASCT2 as prognostic factors

Overview of attention for article published in Breast Cancer Research, October 2017
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Title
Proteomic profiling of breast cancer metabolism identifies SHMT2 and ASCT2 as prognostic factors
Published in
Breast Cancer Research, October 2017
DOI 10.1186/s13058-017-0905-7
Pubmed ID
Authors

Stephan Bernhardt, Michaela Bayerlová, Martina Vetter, Astrid Wachter, Devina Mitra, Volker Hanf, Tilmann Lantzsch, Christoph Uleer, Susanne Peschel, Jutta John, Jörg Buchmann, Edith Weigert, Karl-Friedrich Bürrig, Christoph Thomssen, Ulrike Korf, Tim Beissbarth, Stefan Wiemann, Eva Johanna Kantelhardt

Abstract

Breast cancer tumors are known to be highly heterogeneous and differences in their metabolic phenotypes, especially at protein level, are less well-understood. Profiling of metabolism-related proteins harbors the potential to establish new patient stratification regimes and biomarkers promoting individualized therapy. In our study, we aimed to examine the relationship between metabolism-associated protein expression profiles and clinicopathological characteristics in a large cohort of breast cancer patients. Breast cancer specimens from 801 consecutive patients, diagnosed between 2009 and 2011, were investigated using reverse phase protein arrays (RPPA). Patients were treated in accordance with national guidelines in five certified German breast centers. To obtain quantitative expression data, 37 antibodies detecting proteins relevant to cancer metabolism, were applied. Hierarchical cluster analysis and individual target characterization were performed. Clustering results and individual protein expression patterns were associated with clinical data. The Kaplan-Meier method was used to estimate survival functions. Univariate and multivariate Cox regression models were applied to assess the impact of protein expression and other clinicopathological features on survival. We identified three metabolic clusters of breast cancer, which do not reflect the receptor-defined subtypes, but are significantly correlated with overall survival (OS, p ≤ 0.03) and recurrence-free survival (RFS, p ≤ 0.01). Furthermore, univariate and multivariate analysis of individual protein expression profiles demonstrated the central role of serine hydroxymethyltransferase 2 (SHMT2) and amino acid transporter ASCT2 (SLC1A5) as independent prognostic factors in breast cancer patients. High SHMT2 protein expression was significantly correlated with poor OS (hazard ratio (HR) = 1.53, 95% confidence interval (CI) = 1.10-2.12, p ≤ 0.01) and RFS (HR = 1.54, 95% CI = 1.16-2.04, p ≤ 0.01). High protein expression of ASCT2 was significantly correlated with poor RFS (HR = 1.31, 95% CI = 1.01-1.71, p ≤ 0.05). Our data confirm the heterogeneity of breast tumors at a functional proteomic level and dissects the relationship between metabolism-related proteins, pathological features and patient survival. These observations highlight the importance of SHMT2 and ASCT2 as valuable individual prognostic markers and potential targets for personalized breast cancer therapy. ClinicalTrials.gov, NCT01592825 . Registered on 3 May 2012.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 22%
Student > Ph. D. Student 9 17%
Student > Bachelor 5 9%
Student > Master 5 9%
Professor 3 6%
Other 8 15%
Unknown 12 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 19 35%
Medicine and Dentistry 6 11%
Agricultural and Biological Sciences 6 11%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Psychology 2 4%
Other 6 11%
Unknown 13 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 June 2018.
All research outputs
#19,951,180
of 25,382,440 outputs
Outputs from Breast Cancer Research
#1,657
of 2,054 outputs
Outputs of similar age
#243,484
of 333,588 outputs
Outputs of similar age from Breast Cancer Research
#16
of 21 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,054 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.2. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
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We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.